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http://hdl.handle.net/10553/44294
Título: | Global speed vs. mean travel time. Polynomial dependence analysis in traffic signals optimization using genetic algorithms and parallel computing | Autores/as: | Sánchez-Medina, Javier J. Galán-Moreno, M. J. Rubio-Royo, Enrique |
Clasificación UNESCO: | 120304 Inteligencia artificial 332702 Análisis del trafico |
Palabras clave: | Beowulf cluster Cellular automata microsimulation Genetic algorithms Parallel computing Traffic flow optimization, et al. |
Fecha de publicación: | 2009 | Conferencia: | 2009 International Conference on Artificial Intelligence, ICAI 2009 | Resumen: | In our group we have developed a traffic lights programming optimization model based on the combination of Genetic Algorithms and Microsimulation running over a Beowulf Cluster parallel computer. So far, in this architecture we have used a single variable for the fitness function. In this research our aim is to explore any polynomial dependence - up to a 12 th degree - between two candidate variables as potential participants in the fitness function: Global Speed and the Mean Travel Time. All tests have been fulfilled using data from a real world scenario located in Saragossa, Spain. We have used the supplied traffic lights provided, and also traffic statistics from the zone. | URI: | http://hdl.handle.net/10553/44294 | ISBN: | 978-1-60132-109-1 | Fuente: | Proceedings of the 2009 International Conference on Artificial Intelligence, ICAI 2009, v. 2, p. 980-986 |
Colección: | Actas de congresos |
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